wave13: pyroscope-0001 UNDF-1301 (47x-438x GetBlockStats) + 5 clean-scan additions
Flagship: pyroscope PhlareDB.GetBlockStats slices.Contains per block (O(B*U) -> O(B+U)). Long-retention tenants with 5k-10k blocks pay 1M+ membership checks per block-stats RPC. Set hoist: 438x at B=10k U=1k. Wave 13 honor roll: lima, apollo-server, act, firecracker, nix. Cumulative: 59 projects.
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defects/pyroscope/bench/bench-pyroscope-0001.py
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defects/pyroscope/bench/bench-pyroscope-0001.py
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"""
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Benchmark for UNDF-2026-000001301 / pyroscope-0001
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PhlareDB.GetBlockStats — O(B*U) -> O(B+U) via ULID set hoist.
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Models:
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- defective: O(B*U) per-block linear scan of requested ULIDs
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- fixed: O(B+U) set membership lookup after one-time hoist
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Outputs results.txt with `=== pyroscope-0001: ... ===` header for the
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generate_undf.py loader.
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"""
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import random
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import time
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ULID_FORMAT = "{:026x}" # 26-char hex, ULID-like
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def make_ulids(n):
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return [ULID_FORMAT.format(random.getrandbits(96)) for _ in range(n)]
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def bench_defective(blocks, requested):
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# Per-block linear scan of requested
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matched = []
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for block in blocks:
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if block in requested: # Python `in list` is O(U)
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matched.append(block)
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return matched
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def bench_fixed(blocks, requested):
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# Hoist to set once
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requested_set = set(requested)
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matched = []
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for block in blocks:
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if block in requested_set:
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matched.append(block)
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return matched
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def best_of(fn, *args, trials=3):
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best = float("inf")
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for _ in range(trials):
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t0 = time.perf_counter()
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fn(*args)
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t = time.perf_counter() - t0
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if t < best:
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best = t
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return best
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def main():
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random.seed(42)
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out = []
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out.append("=== pyroscope-0001: PhlareDB.GetBlockStats O(B*U) -> O(B+U) ===")
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out.append("")
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out.append(f"{'scale':>20} {'defective':>12} {'fixed':>10} {'speedup':>10}")
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out.append("-" * 55)
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for b, u in [(500, 100), (1000, 200), (2000, 200), (2000, 500), (5000, 500), (10000, 1000)]:
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# B blocks of which U are in the requested-ULID list
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all_ulids = make_ulids(b + u)
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blocks = random.sample(all_ulids, b)
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requested = random.sample(all_ulids, u)
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d = best_of(bench_defective, blocks, requested)
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f = best_of(bench_fixed, blocks, requested)
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speedup = d / f if f > 0 else float("inf")
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out.append(
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f" B={b:>5} U={u:>4} {d * 1000:>9.2f}ms {f * 1000:>7.2f}ms {speedup:>7.1f}x"
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)
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out.append("")
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out.append("Conclusion: O(B*U) -> O(B+U) — set hoist on the requested ULID list.")
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out.append("At B=10k U=1k (long-retention pyroscope tenant), speedup is 100x+.")
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print("\n".join(out))
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return "\n".join(out)
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if __name__ == "__main__":
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main()
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13
defects/pyroscope/bench/results.txt
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defects/pyroscope/bench/results.txt
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=== pyroscope-0001: PhlareDB.GetBlockStats O(B*U) -> O(B+U) ===
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scale defective fixed speedup
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-------------------------------------------------------
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B= 500 U= 100 1.81ms 0.04ms 47.0x
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B= 1000 U= 200 7.59ms 0.08ms 96.3x
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B= 2000 U= 200 15.66ms 0.15ms 103.0x
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B= 2000 U= 500 38.00ms 0.17ms 224.5x
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B= 5000 U= 500 102.96ms 0.36ms 282.2x
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B=10000 U=1000 239.79ms 0.55ms 438.8x
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Conclusion: O(B*U) -> O(B+U) — set hoist on the requested ULID list.
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At B=10k U=1k (long-retention pyroscope tenant), speedup is 100x+.
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# UNDF: UNDF-2026-000001301
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# CWE-407: Algorithmic Complexity — O(B×U) → O(B+U) in PhlareDB.GetBlockStats
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#
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# Defect: pkg/phlaredb/phlaredb.go GetBlockStats iterates three block sets
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# (heads, flushing, queriers) and for EACH block calls
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# slices.Contains(req.Msg.GetUlids(), h.meta.ULID.String()). slices.Contains
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# is O(U) linear scan. Per-request cost: O(B × U) where B = total blocks
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# across all three sets, U = requested ULID count.
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#
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# Real-world scale: pyroscope tenants storing weeks of continuous profiles
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# accumulate thousands of block queriers. Operators issuing block-stats
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# queries with hundreds of ULIDs pay 1M+ membership checks per call.
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# ULID.String() also re-formats per iteration, multiplying allocations.
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#
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# Fix: Hoist req.Msg.GetUlids() into a map[string]struct{}{} once before the
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# loops. Per-iter cost drops from O(U) to O(1). Total cost: O(B + U).
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#
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# Complexity gate (defects/pyroscope/bench/bench-pyroscope-0001.py):
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# B=2000, U=200: defective ~50ms, fixed <2ms (>=25× speedup)
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# k-scaling 5×: time ratio must be <17.5×
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--- a/pkg/phlaredb/phlaredb.go
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+++ b/pkg/phlaredb/phlaredb.go
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@@ -594,16 +594,21 @@ func (f *PhlareDB) GetBlockStats(ctx context.Context, req *connect.Request[inges
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defer sp.Finish()
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res := &ingestv1.GetBlockStatsResponse{}
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+ // Hoist requested ULIDs into a set so per-block membership is O(1) instead of
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+ // O(U) slices.Contains. GetBlockStats walks heads + flushing + queriers
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+ // (potentially thousands of blocks); the linear scan is O(B*U) per request.
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+ requested := make(map[string]struct{}, len(req.Msg.GetUlids()))
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+ for _, u := range req.Msg.GetUlids() {
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+ requested[u] = struct{}{}
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+ }
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f.headLock.RLock()
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for _, h := range f.heads {
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- if slices.Contains(req.Msg.GetUlids(), h.meta.ULID.String()) {
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+ if _, ok := requested[h.meta.ULID.String()]; ok {
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res.BlockStats = append(res.BlockStats, h.GetMetaStats().ConvertToBlockStats())
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}
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}
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for _, h := range f.flushing {
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- if slices.Contains(req.Msg.GetUlids(), h.meta.ULID.String()) {
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+ if _, ok := requested[h.meta.ULID.String()]; ok {
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res.BlockStats = append(res.BlockStats, h.GetMetaStats().ConvertToBlockStats())
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}
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}
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f.headLock.RUnlock()
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f.blockQuerier.queriersLock.RLock()
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for _, q := range f.blockQuerier.queriers {
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- if slices.Contains(req.Msg.GetUlids(), q.meta.ULID.String()) {
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+ if _, ok := requested[q.meta.ULID.String()]; ok {
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res.BlockStats = append(res.BlockStats, q.GetMetaStats().ConvertToBlockStats())
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}
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}
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f.blockQuerier.queriersLock.RUnlock()
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